Bid farewell to single indicators: Machine learning models integrating multidimensional data lead thrombosis risk prediction into a new stage

doi:10.3748/wjg.118337

Advanced Search

BPG is committed to discovery and dissemination of knowledge

Home / Archive / Volume 32, Issue 34

This Article

(4)

(5)

(0)

(7)

Peer-Review Report of This Article

CrossCheck and Google Search of This Article

Academic Rules and Norms of This Article

Citation of this article

Corresponding Author of This Article

Research Domain of This Article

Article-Type of This Article

Open-Access Policy of This Article

Times Cited Counts in Google of This Article

Journal Information of This Article

Publication Name

World Journal of Gastroenterology

ISSN

1007-9327

Publisher of This Article

Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

Editorial

Copyright: ©Author(s) 2026. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See permissions. Published by Baishideng Publishing Group Inc.

World J Gastroenterol. Sep 14, 2026; 32(34): 118337
Published online Sep 14, 2026. doi: 10.3748/wjg.118337

Open in New Tab Full Size Figure Download Figure

Figure 1 Application path diagram of machine learning model in nonvariceal gastrointestinal bleeding thrombosis risk prediction.

Citation: Su Y, Wang DX, Zhao YQ, Xing X. Bid farewell to single indicators: Machine learning models integrating multidimensional data lead thrombosis risk prediction into a new stage. World J Gastroenterol 2026; 32(34): 118337
URL: https://www.wjgnet.com/1007-9327/full/v32/i34/118337.htm
DOI: https://dx.doi.org/10.3748/wjg.118337

Su Y, Wang DX, Zhao YQ, Xing X. Bid farewell to single indicators: Machine learning models integrating multidimensional data lead thrombosis risk prediction into a new stage. World J Gastroenterol 2026; 32(34): 118337 [DOI: 10.3748/wjg.118337]

All content on this site: Copyright © 1993-2026 Baishideng Publishing Group Inc, its licensors, and contributors. All rights are reserved, including those for text and data mining, AI training, and similar technologies. For all open access content, the relevant licensing terms apply.